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Journal Article

Citation

Tabone W, Happee R, Garcia J, Lee YM, Lupetti ML, Merat N, de Winter J. Transp. Res. F Traffic Psychol. Behav. 2023; 94: 170-189.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.trf.2023.02.005

PMID

unavailable

Abstract

Augmented Reality (AR) technology could be utilised to assist pedestrians in navigating safely through traffic. However, whether potential users would understand and use such AR solutions is currently unknown. Nine novel AR interfaces for pedestrian-vehicle communication, previously developed using an experience-based design method, were evaluated through an online questionnaire study completed by 992 respondents in Germany, the Netherlands, Norway, Sweden, and the United Kingdom. The AR indicated whether it was safe to cross the road in front of an approaching automated vehicle. Each interface was rated for its intuitiveness and convincingness, aesthetics, and usefulness. Moreover, comments were collected for qualitative analysis. The results indicated that interfaces that employed traditional design elements from existing traffic, and head-up displays, received the highest ratings overall. Statistical results also showed that there were no significant effects of country, age, and gender on interface acceptance. Thematic analysis of the textual comments offered detail on each interface design's stronger and weaker points, and revealed unintended effects of certain designs. In particular, some of the interfaces were commented on as being dangerous or scary, or were criticised that they could be misinterpreted in that they signal that something is wrong with the vehicle, or that they could occlude the view of the vehicle. The current findings highlight the limitations of experience-based design, and the importance of applying legacy design principles and involving target users in design and evaluation. Future research should be conducted in scenarios in which pedestrians actually interact with approaching vehicles.


Language: en

Keywords

Augmented reality; Automated vehicles; Online questionnaire; Pedestrian-vehicle interactions; Road crossing; User study; Vulnerable road users

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